Mohammad Hossein Rohban

The paper identifies a mitochondrial localization phenotype in psychosis patients and uses a cell-based assay to screen for compounds and genes affecting this phenotype.

VarDrug predicts variant-drug interactions using machine learning on PharmGKB data, achieving 90% F1 score for psychiatric disorder applications.

The paper compares morphology and gene expression data to determine their complementary roles in mapping cell states across drug perturbations.

The paper identifies small molecule regulators of biological pathways by matching compound effects to known pathway phenotypes in public cell image data.

The paper introduces a cloud-based platform for analyzing calcium activity in motor neurons to identify compounds that reverse disease phenotypes in amyotrophic lateral sclerosis.

The paper improves image-based profiling by fusing data to capture cell heterogeneity, enhancing prediction of compound mechanisms of action and gene pathways by ~20%.

The paper uses morphological profiling to identify gene function and connectivity, revealing TRAF2/C-REL's negative regulation of Hippo pathway effectors.